Different results from Original Tensorflow model and Inference from NCS

I have been getting wrong results in comparison with the original tensorflow model. I followed the guidance to create the tensorflow model without unneccesary layers (such as dropout) and the created model works perfectly when predicted with GPU. Then once I create the freeze graph, and use it to predict my dataset, i get completely different results. The things is that mvNCCheck passes every test(see below details). But the graph created with mvNCCompile produces completely wrong results. Kindly help me on this.

Obtained Global Sum Difference: 0.011809378862380981**

Comments

Hi @sangathamilan
What application are you using? Can you provide the code you're using? I'd like to try to reproduce this issue to see what kind of results I'm getting. Bad results sometimes mean there could be an error in the pre processing.